scholarly journals Examining which clinicians provide admission hospital care in a high mortality setting and their adherence to guidelines: an observational study in 13 hospitals

2020 ◽  
Vol 105 (7) ◽  
pp. 648-654 ◽  
Author(s):  
Morris Ogero ◽  
Samuel Akech ◽  
Lucas Malla ◽  
Ambrose Agweyu ◽  
Grace Irimu ◽  
...  
Keyword(s):  
High Mortality ◽  
Guideline Adherence ◽  
Medical Officer ◽  
Severity Of Illness ◽  
Clinical Officer ◽  
Data Set ◽  
Experiential Training ◽  
Training Performance ◽  
Logistic Regression Models

BackgroundWe explored who actually provides most admission care in hospitals offering supervised experiential training to graduating clinicians in a high mortality setting where practices deviate from guideline recommendations.MethodsWe used a large observational data set from 13 Kenyan county hospitals from November 2015 through November 2018 where patients were linked to admitting clinicians. We explored guideline adherence after creating a cumulative correctness of Paediatric Admission Quality of Care (cPAQC) score on a 5-point scale (0–4) in which points represent correct, sequential progress in providing care perfectly adherent to guidelines comprising admission assessment, diagnosis and treatment. At the point where guideline adherence declined the most we dichotomised the cPAQC score and used multilevel logistic regression models to explore whether clinician and patient-level factors influence adherence.ResultsThere were 1489 clinicians who could be linked to 53 003 patients over a period of 3 years. Patients were rarely admitted by fully qualified clinicians and predominantly by preregistration medical officer interns (MOI, 46%) and diploma level clinical officer interns (COI, 41%) with a median of 28 MOI (range 11–68) and 52 COI (range 5–160) offering care per study hospital. The cPAQC scores suggest that perfect guideline adherence is found in ≤12% of children with malaria, pneumonia or diarrhoea with dehydration. MOIs were more adherent to guidelines than COI (adjusted OR 1.19 (95% CI 1.07 to 1.34)) but multimorbidity was significantly associated with lower guideline adherence.ConclusionOver 85% of admissions to hospitals in high mortality settings that offer experiential training in Kenya are conducted by preregistration clinicians. Clinical assessment is good but classifying severity of illness in accordance with guideline recommendations is a challenge. Adherence by MOI with 6 years’ training is better than COI with 3 years’ training, performance does not seem to improve during their 3 months of paediatric rotations.

scholarly journals Transfers among Long-term Nursing Home Residents during the COVID-19 Pandemic

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 733-733
Author(s):  
Ana Montoya ◽  
Chiang-Hua Chang ◽  
Pil Park ◽  
Julie Bynum
Keyword(s):  
Risk Factors ◽  
Nursing Home ◽  
Nursing Homes ◽  
Functional Decline ◽  
Nursing Home Residents ◽  
Data Set ◽  
Transfer Rates ◽  
Logistic Regression Models

Abstract Transferring long-term nursing home residents between facilities can compromise the quality of life and be associated with functional decline, hospitalizations, and even death. This study aimed to examine transfer rates and identify risk factors associated with transfers among long-term nursing home residents before (2018-2019) and during the COVID-19 pandemic (2020). Using the Michigan state Minimum Data Set data 2018-2020, we identified long-term residents as those who stayed in nursing homes for at least 100 days each year (N=39,693, 39,454, and 35,575, respectively). We defined a facility-to-facility transfer as a direct transfer between two nursing homes. We first examined the likelihood of transfer by year using logistic regression models, adjusting for residents’ age, sex, race, and marital status. We then examined two health statuses that could be associated with a transfer: activities of daily living (ADL) and cognitive impairment. Finally, we compared transfers that occurred before COVID-19 (2018-2019) and during COVID-19 (2020), adjusting for residents’ demographic characteristics and health statuses. After adjustment, age was the only factor associated with transfers for all three years (Age>=80: AOR=0.61, 95% CI: 0.54-0.69; AOR=0.63, 95% CI: 0.55-0.72; AOR=0.71, 95% CI: 0.63-0.80, respectively). New risk factors in 2020 were Black race (AOR=1.22, 95% CI: 1.07-1.40) and requiring ADL assistance (AOR=1.24, 95% CI: 1.03-1.49). The COVID-19 period had higher transfer rate (unadjusted rates 2.9%, 2.7%, 3.5%, respectively) with 10% higher odds of transfer compared to before COVID-19 (AOR=1.10, 95% CI: 1.01-1.20). This finding suggests that COVID-19 has an impact on how nursing home transferred their long-term residents.

scholarly journals Calling for improved quality in the registration of traditional Chinese medicine during the public health emergency: a survey of trial registries for COVID-19, H1N1, and SARS

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Zhuoran Kuang ◽  
◽  
Xiaoyan Li ◽  
Jianxiong Cai ◽  
Yaolong Chen ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Secondary Outcome ◽  
Specific Information ◽  
Clinical Trial Registry ◽  
Data Set ◽  
Diagnosis Criteria

Abstract Objective To assess the registration quality of traditional Chinese medicine (TCM) clinical trials for COVID-19, H1N1, and SARS. Method We searched for clinical trial registrations of TCM in the WHO International Clinical Trials Registry Platform (ICTRP) and Chinese Clinical Trial Registry (ChiCTR) on April 30, 2020. The registration quality assessment is based on the WHO Trial Registration Data Set (Version 1.3.1) and extra items for TCM information, including TCM background, theoretical origin, specific diagnosis criteria, description of intervention, and outcomes. Results A total of 136 records were examined, including 129 severe acute respiratory syndrome coronavirus 2 (COVID-19) and 7 H1N1 influenza (H1N1) patients. The deficiencies in the registration of TCM clinical trials (CTs) mainly focus on a low percentage reporting detailed information about interventions (46.6%), primary outcome(s) (37.7%), and key secondary outcome(s) (18.4%) and a lack of summary result (0%). For the TCM items, none of the clinical trial registrations reported the TCM background and rationale; only 6.6% provided the TCM diagnosis criteria or a description of the TCM intervention; and 27.9% provided TCM outcome(s). Conclusion Overall, although the number of registrations of TCM CTs increased, the registration quality was low. The registration quality of TCM CTs should be improved by more detailed reporting of interventions and outcomes, TCM-specific information, and sharing of the result data.

Simple Index to Assess the Calibration Quality of Safety Performance Functions Based on Multiple Goodness-of-Fit Metrics

2021 ◽  
pp. 036119812110088
Author(s):  
Raul E. Avelar ◽  
Karen Dixon ◽  
Boniphace Kutela ◽  
Sam Klump ◽  
Beth Wemple ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Synthetic Data ◽  
Calibration Procedure ◽  
Safety Performance ◽  
Absolute Deviation ◽  
Data Set ◽  
Safety Database ◽  
Simple Index ◽  
Safety Performance Functions

The calibration of safety performance functions (SPFs) is a mechanism included in the Highway Safety Manual (HSM) to adjust SPFs in the HSM for use in intended jurisdictions. Critically, the quality of the calibration procedure must be assessed before using the calibrated SPFs. Multiple resources to aid practitioners in calibrating SPFs have been developed in the years following the publication of the HSM 1st edition. Similarly, the literature suggests multiple ways to assess the goodness-of-fit (GOF) of a calibrated SPF to a data set from a given jurisdiction. This paper uses the calibration results of multiple intersection SPFs to a large Mississippi safety database to examine the relations between multiple GOF metrics. The goal is to develop a sensible single index that leverages the joint information from multiple GOF metrics to assess overall quality of calibration. A factor analysis applied to the calibration results revealed three underlying factors explaining 76% of the variability in the data. From these results, the authors developed an index and performed a sensitivity analysis. The key metrics were found to be, in descending order: the deviation of the cumulative residual (CURE) plot from the 95% confidence area, the mean absolute deviation, the modified R-squared, and the value of the calibration factor. This paper also presents comparisons between the index and alternative scoring strategies, as well as an effort to verify the results using synthetic data. The developed index is recommended to comprehensively assess the quality of the calibrated intersection SPFs.

Challenging the Link Between Early Childhood Television Exposure and Later Attention Problems: A Multiverse Approach

2021 ◽  
pp. 095679762097165
Author(s):  
Matthew T. McBee ◽  
Rebecca J. Brand ◽  
Wallace E. Dixon
Keyword(s):  
Early Childhood ◽  
Regression Models ◽  
Propensity Score Analysis ◽  
Harmful Effect ◽  
Attention Problems ◽  
Linear Regression Models ◽  
Data Set ◽  
Logistic Regression Models ◽  
Score Analysis ◽  
Television Exposure

In 2004, Christakis and colleagues published an article in which they claimed that early childhood television exposure causes later attention problems, a claim that continues to be frequently promoted by the popular media. Using the same National Longitudinal Survey of Youth 1979 data set ( N = 2,108), we conducted two multiverse analyses to examine whether the finding reported by Christakis and colleagues was robust to different analytic choices. We evaluated 848 models, including logistic regression models, linear regression models, and two forms of propensity-score analysis. If the claim were true, we would expect most of the justifiable analyses to produce significant results in the predicted direction. However, only 166 models (19.6%) yielded a statistically significant relationship, and most of these employed questionable analytic choices. We concluded that these data do not provide compelling evidence of a harmful effect of TV exposure on attention.

scholarly journals Ownership Variation in Violated Regulations and National Care Standards: Evidence From Social Care Providers

2021 ◽  
pp. 089976402110014
Author(s):  
Anders M. Bach-Mortensen ◽  
Ani Movsisyan
Keyword(s):  
Social Care ◽  
Negative Binomial ◽  
Third Sector ◽  
Care Providers ◽  
Data Set ◽  
Logistic Regression Models ◽  
For Profit ◽  
Care Services ◽  
Significant Difference ◽  
Research Gap

Social care services are increasingly provisioned in quasi-markets in which for-profit, public, and third sector providers compete for contracts. Existing research has investigated the implications of this development by analyzing ownership variation in latent outcomes such as quality, but little is known about whether ownership predicts variation in more concrete outcomes, such as violation types. To address this research gap, we coded publicly available inspection reports of social care providers regulated by the Care Inspectorate in Scotland and created a novel data set enabling analysis of ownership variation in violations of (a) regulations, and (b) national care standards over an entire inspection year ( n = 4,178). Using negative binomial and logistic regression models, we find that for-profit providers are more likely to violate non-enforceable outcomes (national care standards) relative to other ownership types. We did not identify a statistically significant difference between for-profit and third sector providers with regard to enforceable outcomes (regulations).

scholarly journals Leveraging Road Characteristics and Contributor Behaviour for Assessing Road Type Quality in OSM

2021 ◽  
Vol 10 (7) ◽  
pp. 436
Author(s):  
Amerah Alghanim ◽  
Musfira Jilani ◽  
Michela Bertolotto ◽  
Gavin McArdle
Keyword(s):  
Machine Learning ◽  
Spatial Data ◽  
Classification Accuracy ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Data Set ◽  
Semantic Inference ◽  
Road Type ◽  
The Impact

Volunteered Geographic Information (VGI) is often collected by non-expert users. This raises concerns about the quality and veracity of such data. There has been much effort to understand and quantify the quality of VGI. Extrinsic measures which compare VGI to authoritative data sources such as National Mapping Agencies are common but the cost and slow update frequency of such data hinder the task. On the other hand, intrinsic measures which compare the data to heuristics or models built from the VGI data are becoming increasingly popular. Supervised machine learning techniques are particularly suitable for intrinsic measures of quality where they can infer and predict the properties of spatial data. In this article we are interested in assessing the quality of semantic information, such as the road type, associated with data in OpenStreetMap (OSM). We have developed a machine learning approach which utilises new intrinsic input features collected from the VGI dataset. Specifically, using our proposed novel approach we obtained an average classification accuracy of 84.12%. This result outperforms existing techniques on the same semantic inference task. The trustworthiness of the data used for developing and training machine learning models is important. To address this issue we have also developed a new measure for this using direct and indirect characteristics of OSM data such as its edit history along with an assessment of the users who contributed the data. An evaluation of the impact of data determined to be trustworthy within the machine learning model shows that the trusted data collected with the new approach improves the prediction accuracy of our machine learning technique. Specifically, our results demonstrate that the classification accuracy of our developed model is 87.75% when applied to a trusted dataset and 57.98% when applied to an untrusted dataset. Consequently, such results can be used to assess the quality of OSM and suggest improvements to the data set.

scholarly journals Novel Assistive Device for Tomographic Ultrasound Neck Imaging vs. Freehand

2020 ◽  
Vol 6 (3) ◽  
pp. 28-31
Author(s):  
Marcel Köhler ◽  
Elmer Jeto Gomes Ataide ◽  
Jens Ziegle ◽  
Axel Boese ◽  
Michael Friebe
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Diagnostic Procedures ◽  
Assistive Device ◽  
Volume Data ◽  
Data Set ◽  
Scanning Method ◽  
Neck Area ◽  
2D Ultrasound

AbstractFor assessing clinically relevant structures in the neck area, especially the thyroid, it has been shown that 3D or tomographic ultrasound (3D US or tUS) is able to outperform standard 2D ultrasound [1] and computed tomography [2] for certain diagnostic procedures. However, when using a freehand and unassisted scanning method to acquire a 3D US volume data set in this area overlapping image slices, a variation of the probe angulation or differences in training might lead to unusable scanning results. Based on previous works [3] [4] we propose the design - with subsequent testing - of an assistive device that is able to aid physicians during the tUS scanning process on the neck. To validate the feasibility and efficacy we compared the image quality of both freehand and assisted scanning.

Cost effectiveness in palliative care setting

2018 ◽  
Vol 21 (2) ◽  
pp. 62-71
Author(s):  
Henry O’Lawrence ◽  
Rohan Chowlkar
Keyword(s):  
Quality Of Life ◽  
Palliative Care ◽  
End Of Life ◽  
Hospice Care ◽  
Home Health ◽  
Data Set ◽  
Content Type ◽  
Care Services ◽  
The Cost

Purpose The purpose of this paper is to determine the cost effectiveness of palliative care on patients in a home health and hospice setting. Secondary data set was utilized to test the hypotheses of this study. Home health care and hospice care services have the potential to avert hospital admissions in patients requiring palliative care, which significantly affects medicare spending. With the aging population, it has become evident that demand of palliative care will increase four-fold. It was determined that current spending on end-of-life care is radically emptying medicare funds and fiscally weakening numerous families who have patients under palliative care during life-threatening illnesses. The study found that a majority of people registering for palliative and hospice care settings are above the age group of 55 years old. Design/methodology/approach Different variables like length of stay, mode of payment and disease diagnosis were used to filter the available data set. Secondary data were utilized to test the hypothesis of this study. There are very few studies on hospice and palliative care services and no study focuses on the cost associated with this care. Since a very large number of the USA, population is turning 65 and over, it is very important to analyze the cost of care for palliative and hospice care. For the purpose of this analysis, data were utilized from the National Home and Hospice Care Survey (NHHCS), which has been conducted periodically by the Centers for Disease Control and Prevention’s National Center for Health Statistics. Descriptive statistics, χ2 tests and t-tests were used to test for statistical significance at the p<0.05 level. Findings The Statistical Package for Social Sciences (SPSS) was utilized for this result. H1 predicted that patients in the age group of 65 years and up have the highest utilization of home and hospice care. This study examined various demographic variables in hospice and home health care which may help to evaluate the cost of care and the modes of payments. This section of the result presents the descriptive analysis of dependent, independent and covariate variables that provide the overall national estimates on differences in use of home and hospice care in various age groups and sex. Research limitations/implications The data set used was from the 2007 NHHCS survey, no data have been collected thereafter, and therefore, gap in data analysis may give inaccurate findings. To compensate for this gap in the data set, recent studies were reviewed which analyzed cost in palliative care in the USA. There has been a lack of evidence to prove the cost savings and improved quality of life in palliative/hospice care. There is a need for new research on the various cost factors affecting palliative care services as well as considering the quality of life. Although, it is evident that palliative care treatment is less expensive as compared to the regular care, since it eliminates the direct hospitalization cost, but there is inadequate research to prove that it improves the quality of life. A detailed research is required considering the additional cost incurred in palliative/hospice care services and a cost-benefit analysis of the same. Practical implications While various studies reporting information applicable to the expenses and effect of family caregiving toward the end-of-life were distinguished, none of the previous research discussed this issue as their central focus. Most studies addressed more extensive financial effect of palliative and end-of-life care, including expenses borne by the patients themselves, the medicinal services framework and safety net providers or beneficent/willful suppliers. This shows a significant hole in the current writing. Social implications With the aging population, it has become evident that demand of palliative/hospice care will increase four-fold. The NHHCS have stopped keeping track of the palliative care requirements after 2007, which has a negative impact on the growing needs. Cost analysis can only be performed by analyzing existing data. This review has recognized a huge niche in the evidence base with respect to the cost cares of giving care and supporting a relative inside a palliative/hospice care setting. Originality/value The study exhibited that cost diminishments in aggressive medications can take care of the expenses of palliative/hospice care services. The issue of evaluating result in such a physically measurable way is complicated by the impalpable nature of large portions of the individual components of outcome. Although physical and mental well-being can be evaluated to a certain degree, it is significantly more difficult to gauge in a quantifiable way, the social and profound measurements of care that help fundamentally to general quality of care.

Physician Perceptions on Quality of Life and Resuscitation Preferences for Extremely Early Newborns

2021 ◽  
Author(s):  
Danielle LoRe ◽  
Christopher Mattson ◽  
Dalia M. Feltman ◽  
Jessica T. Fry ◽  
Kathleen G. Brennan ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Logistic Regression ◽  
Regression Models ◽  
Mixed Effects ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Comfort Care ◽  
Logistic Regression Models ◽  
Extremely Preterm

Objective The study aimed to explore physician views on whether extremely early newborns will have an acceptable quality of life (QOL), and if these views are associated with physician resuscitation preferences. Study Design We performed a cross-sectional survey of neonatologists and maternal fetal medicine (MFM) attendings, fellows, and residents at four U.S. medical centers exploring physician views on future QOL of extremely early newborns and physician resuscitation preferences. Mixed-effects logistic regression models examined association of perceived QOL and resuscitation preferences when adjusting for specialty, level of training, gender, and experience with ex-premature infants. Results A total of 254 of 544 (47%) physicians were responded. A minority of physicians had interacted with surviving extremely early newborns when they were ≥3 years old (23% of physicians in pediatrics/neonatology and 6% in obstetrics/MFM). The majority of physicians did not believe an extremely early newborn would have an acceptable QOL at the earliest gestational ages (11% at 22 and 23% at 23 weeks). The majority of physicians (73%) believed that having an extremely preterm infant would have negative effects on the family's QOL. Mixed-effects logistic regression models (odds ratio [OR], 95% confidence interval [CI]) revealed that physicians who believed infants would have an acceptable QOL were less likely to offer comfort care only at 22 (OR: 0.19, 95% CI: 0.05–0.65, p < 0.01) and 23 weeks (OR: 0.24, 95% CI: 0.07–0.78, p < 0.02). They were also more likely to offer active treatment only at 24 weeks (OR: 9.66, 95% CI: 2.56–38.87, p < 0.01) and 25 weeks (OR: 19.51, 95% CI: 3.33–126.72, p < 0.01). Conclusion Physician views of extremely early newborns' future QOL correlated with self-reported resuscitation preferences. Residents and obstetric physicians reported more pessimistic views on QOL. Key Points

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